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Newton Howard

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{AFC submission|d|dup|Newton Howard|u=Bbrink8|ns=2|decliner=Robert McClenon|declinets=20151226181205|ts=20151226174845}}

  • Comment: Previous draft has been deleted as abandoned. Please add references and resubmit. Robert McClenon (talk) 21:00, 26 December 2015 (UTC)
  • Comment: On further review, the existing draft in draft space, which is mostly an autobiography, has been abandoned for more than six months. The author of this draft is advised to add proper references, because this draft is unreferenced, and otherwise to wait until the existing draft is speedy-deleted as abandoned. Robert McClenon (talk) 18:15, 26 December 2015 (UTC)
  • Comment: The author may have accidentally created two copies of this draft. The one in draft space is a good start but is unreferenced and should be the basis for more work (entry of references). I suggest that this one be deleted or blanked so that edits do not get split between the two drafts. Robert McClenon (talk) 18:12, 26 December 2015 (UTC)

Prof. Newton Howard is a brain and cognitive scientist and former Director of the MIT Mind Machine Project[1][2] at the Massachusetts Institute of Technology (MIT). He is currently the Professor of Computational Neuroscience and Functional Neurosurgery[3] at the University of Oxford, where he directs the Oxford Computational Neuroscience Laboratory[4]. He is also the Director of the Synthetic Intelligence Lab at MIT[5], the founder of the Center for Advanced Defense Studies[6] and the Chairman of the Brain Sciences Foundation[7]. Professor Howard is also a Senior Fellow at the John Radcliffe Hospital at Oxford, a Senior Scientist at INSERM in Paris and a P.A.H. at the CHU Hospital in Martinique.

His research areas include Cognition, Memory, Trauma, Machine Learning, Comprehensive Brain Modeling, Natural Language Processing, Nanotech, Medical Devices and Artificial Intelligence.

Education

Dr. Howard earned his B.A. from Concordia University, then obtained an M.A. in Technology from Eastern Michigan University. He went on to continue his studies at the University of Oxford where as a graduate member of the Faculty of Mathematical Sciences he proposed the Theory of Intention Awareness (IA)[8], which made a significant impact on the design of command & control systems and information exchange systems at tactical, operational and strategic levels. He further developed this theory at the University of Paris-Sorbonne, where he received a Doctorate in Cognitive Informatics and Mathematics and was awarded the prestigious Habilitation a Diriger des Recherches for his work on the Physics of Cognition (PoC).

Career

Professor Howard is an author and national security advisor[9][10] to several U.S. Government organizations[11]. He has directed leading international cooperation programs on emerging trends in global security and information assurance and has been instrumental in the creation of National Centers of Excellence in medicine, psychiatry, and computation at multiple research institutions in the US. His work has contributed to more than 30 U.S. patents and over 90 publications, fully half of which are in the areas of cognitive and computational theory.

In 2009, Prof. Howard founded the Brain Sciences Foundation (BSF)[7], a nonprofit 501(c)3 organization to help fund research and promote awareness for combating neurological and neurodegenerative diseases. The foundation provides grants and scholarships to support the development and promotion of several highly promising new diagnostic and therapeutic technologies. The organization includes a multitude of fellows from various leading research institutions, including Oxford University, Massachusetts Institute of Technology, La Sorbonne University of Paris and INSERM. The goal of the Foundation is to improve the quality of life for those suffering from neurological disorders.

Research

Prof. Howard's initial work focused on intentionality within the individual and various formal and informal command structures. His Theory of Intention Awareness (IA)[12] is grounded in the systematic design and construction of naturalistic systems and serves as a possible model for explaining volition in human intelligence, recursively throughout all layers of biological organization. Conceptually, IA informs intelligent action planning; being both the process and product of planning and becomes the intelligent architecture to which we can credit purposeful action. This work on Intention Awareness led him to expand his research into signal processing, linguistic analysis and Artificial Intelligence (AI), eventually bringing him to MIT.

While at MIT, he developed the Mood State Indicator (MSI)[13] a system that can model and explain the mental processes involved in human speech and writing to predict emotional states (2011). He next developed the Language Axiological Input/Output system (LXIO)[13] as a practical application of the Mood Sate Indicator technology. LXIO is a system capable of detecting both sentiment and mood states based on the analysis of written or verbal discourse, representing a patient’s mood state by the sum of values generated by a given sentence or word string. LXIO parses sentences into words that are processed through modules to evaluate cognitive states. Words are then processed through time orientation, contextual-prediction and consequent modules and each word's context and grammatical function is computed with the use of a Mind Default Axiology (MDA). Within the LXIO, a learning algorithm tracks patients’ word analysis histories to further enhance accuracy. The significance of LXIO is its ability to incorporate conscious thought and bodily expression (linguistic or otherwise) into a uniform code schema[13].

While at the University of Oxford, Professor Howard turned his focus to neurology, neurosurgery, nanoscale medical devices and biological coprocessors.[14] In 2012, he published and patented[15] the Fundamental Code Unit (FCU)[16] theory, which uses unitary mathematics (ON/OFF +/-) to correlate networks of neurophysiological processes and map them to higher order function. The FCU provides the underlying foundation for the Brain Code (BC) theory, also proposed by Prof. Howard, and is used to map entire circuits of neurological activity to behavior and response, effectively decoding the language of the brain[17].

Professor Howard has worked on various nanoscale Deep Brain Stimulation and optogenetic technologies and in 2014 discovered a functional endogenous optical network within the brain, mediated by neuropsin (OPN5). Within this sub-neural network, photonic activity is transduced into synaptic membrane potential changes within neocortical networks via a cGMP-dependent mechanism, accompanied by a photostimulation-catalyzed G protein/cGMP phosphodiesterase activation, which regulates membrane potential by closing cGMP-gated ion channels. This self-regulating cycle of photon-mediated events in the neocortex involves sequential interactions among 3 mitochondrial sources of endogenously-generated photons during periods of increased neural spiking activity: (a) near-UV photons (~380 nm), a free radical reaction byproduct; (b) blue photons (~470 nm) emitted by NAD(P)H upon absorption of near-UV photons; and (c) green photons (~530 nm) generated by NAD(P)H oxidases, upon NAD(P)H-generated blue photon absorption.  Neuropsin (OPN5) has two switchable conformations (~380nm-absorbing and ~470nm-absorbing), allowing it to serve as an effective regulatory signaling mechanism. The bistable nature of this nanoscale quantum process provides evidence for an on/off (UNARY +/-) coding system existing at the most fundamental level of brain operation and provides a solid neurophysiological basis for the FCU[16] to build from.

Several of these theories have been recently brought to clinical trial and use, beginning with a wearable neurodiagnostic system that uses synchronous multimodal data capture techniques in combination with the FCU to establish a highly comprehensive patient profile that can be securely analyzed against millions of other profiles to find disease biomarkers. The system has demonstrated the ability to diagnose a number of formerly undiagnosable neurodegenerative conditions[18][19], including Alzheimer's Disease (AD) and Parkinson's Disease (PD).[20][17][21]

Selected Works

Patents (US)

Patents (International)

References

  1. ^ "MIT Mind Machine Project". Mind Machine Project. Massachusetts Institute of Technology.
  2. ^ Chandler, David (December 7, 2009). "Rethinking artificial intelligence". MIT News. Massachusetts Institute of Technology.
  3. ^ "Nuffield Department of Surgical Sciences". Nuffield Department of Surgical Sciences. University of Oxford.
  4. ^ "Oxford Computational Neuroscience Laboratory". Oxford Computational Neuroscience Laboratory. University of Oxford.
  5. ^ "Synthetic Intelligence Lab". Synthetic Intelligence Lab. Massachusetts Institute of Technology.
  6. ^ "Center for Advanced Defense Studies". Center for Advanced Defense Studies. Center for Advanced Defense Studies.
  7. ^ a b "Brain Sciences Foundation". Brain Sciences Foundation. Brain Sciences Foundation.
  8. ^ Newton Howard, “Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions", Author House First Books Library, Bloomington, Indiana. 2002.
  9. ^ JMO, CWID (2007). "CWID - Coalition Warrior Interoperability Demonstration" (PDF). CWID JMO.
  10. ^ NATO, MIP (2007). "Joint C3 Information Exchange Data Model Overview" (PDF). MIP-NATO Management Board.
  11. ^ Howard, Newton (2013). "Development of a Diplomatic, Information, Military, Health, and Economic Effects Modeling System" (PDF). Massachusetts Institute of Technology.
  12. ^ Howard, Newton (2002). Theory of Intention Awareness in Tactical Military Intelligence: Reducing Uncertainty by Understanding the Cognitive Architecture of Intentions. Bloomington, IN: Author House First Books Library.
  13. ^ a b c Howard, Newton; Guidere, Mathieu (January 2012). "LXIO: The Mood Detection Robopsych". Brain Sciences Journal.
  14. ^ "Biological Coprocessors". Biological Coprocessors. Biological Coprocessors, Inc.
  15. ^ Howard, Newton. "Patent US20130338526-A1". Google Patent DB. US Patent & Trademark Office.
  16. ^ a b Howard, Newton (2012). "Brain Language: The Fundamental Code Unit" (PDF). Brain Sciences Journal. Brain Sciences Foundation.
  17. ^ a b Howard, Newton (2015). The Brain Language. London, UK: Cambridge Scientific Publishing. ISBN 978-1-908106-50-6.
  18. ^ Howard, Newton; Bergmann, J.; Stein, J. (2013). "Combined Modality of the Brain Code Approach for Early Detection and the Long-term Monitoring of Neurodegenerative Processes". Frontiers Special Issue INCF: Imaging the Brain at Different Scales.
  19. ^ Howard, Newton; Stein, J. (2011). "Computational Methods for Clinical Applications: An Introduction". Functional Neurology, Rehabilitation and Ergonomics.
  20. ^ Howard, Newton (2015). Approach to Study the Brain: Towards the Early Detection of Neurodegenerative Disease. London, UK: Cambridge Scientific Publishing. ISBN 978-1-908106-49-0.
  21. ^ Howard, Newton; Stein, J. F. (2015). "Mathematical Review for Cortical Computing Proposition for Brain Code Hypothesis". Frontiers Systems Neuroscience.
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